Advertising Medium Determination Device and Method Therefor

ABSTRACT

It is also an object of the present invention to provide objective advertisement plan(s). The target specifying information storage part  202  stores information for specifying target attribution including information for specifying information delivery medium of an object to contact with correspondently with searchers&#39; id. The search term storage part  203  correspondently stores a searcher&#39;s id, the timing of search, and the term used for the search. The extraction part  204  extracts the timing of search for such search term for each searcher&#39;s id, segments the extracted search timing for each searcher&#39;s id into a predetermined number in chronological order and then extracts searcher&#39;s id belonging to each segment. The advertising medium data determination part  205  extracts information on candidate of information delivery medium for the each segment from the extracted each searcher&#39;s id using information for specifying a target and determines candidate(s) of information delivery medium from the extracted candidate of information delivery medium.

This application is a continuation application of application Ser. No.13/312,509, filed Dec. 6, 2011, which is a divisional application ofapplication Ser. No. 12/518,817, filed Jun. 11, 2009, which is anational phase application of PCT/JP2008/067493, filed Sep. 26, 2008,the entireties of which are incorporated herein by reference.

TECHNICAL FIELD

The present invention relates to a device for determining advertisingmedium, specifically to a process for determining an advertising medium.

BACKGROUND ART

It is desired to run an advertisement in a sequence of an advertisingmedia to be contacted with a cutting edge demographic, then that for aless cutting edge demographic and then that for a demographic ofordinary people from the viewpoint of advertisement effect becausemerchandises and services depends on the trends.

Under the circumstances, a method in which an advertisement plan iscreated by referring to a previously conducted questionnaire onattributions for the demographics such as “very sensitive to thefashion”, “sensitive to the fashion” and “insensitive to the fashion”has been employed.

DISCLOSURE OF THE INVENTION Problem to be Solved by the Invention

However, it is depending upon merchandise or services whether arespondent(s) of a questionnaire belonging to the cutting edgedemographic. In addition, even when a respond(s) from the questionnaireis stored for each questionnaire responder, such evaluation is verysubjective to each responder.

It is an object of the present invention to provide an advertisingmedium determination device capable of subjectively determiningadvertising medium and the timing of running such advertisement byutilizing search results using search engines on the Internet.

The characteristics, usage(s), advantage(s) of the present inventionwill be apparent from the embodiments herein and appended figures.

Means for Solving the Problem

1) The advertising medium determination device according to theinvention comprising: 1) target specifying information storage means forstoring correspondently with searchers' identification (ID) informationfor specifying target attribution including information for specifyinginformation delivery medium of an object to contact with; 2) search termstorage means for correspondently storing searchers' IDs, timing ofsearch and search terms used for the search; 3) extraction means forextracting a timing of search for a search term for each searcher's IDfrom the search term storage means when the search term is provided as asearch condition and segmenting the extracted search timing into apredetermined number in chronological order and extracting searcher's IDbelonging to each segment; and 4) advertising medium data determinationmeans for extracting candidates of information delivery medium for theeach segment from the extracted each searcher's ID using information forspecifying a target stored in the target specifying information storagemeans for determining one or more than two representation candidates ofinformation delivery medium from the extracted candidates of informationdelivery medium, thereby determining the representation candidates ofinformation delivery medium arranged in chronological order asadvertising medium data in a name of advertising object providedcorrespondently to the search term. In this way, it is possible todetermine chronological order of the advertising medium by segmentingeach of the searchers for the search timing of search term in the pastand by further referencing information delivery medium of an object tocontact with by the searcher belonging to each of the segments.

2) The advertising medium determination device according to theinvention, further comprising: search term specification means forspecifying a search term corresponding to the name of advertising objectand providing the specified search term to the extraction means whileproviding a term corresponding to the name of advertising object to theadvertising medium data determination means when such term is providedthereto. In this way, when a term corresponding to the advertisingmedium is provided, a search term corresponding to the name ofadvertising object can be provided.

3) The advertising medium determination device according to theinvention, wherein the search term stored in the search term storagemeans is classified into categories, and wherein the search termspecification means specifies a search term of a category into which aterm corresponding to the name of advertising object belong thereto. Inthis way, a search term in a category belonging to a term correspondingto the name of advertising object can be provided.

4) The advertising medium determination device according to theinvention, further comprising: search number variation historycalculation means for calculating variation history of search numberrepresenting chronological variation of the number of search for eachsearch term stored in the search term storage means; and search numbervariation history storage means for storing variation history of thenumber of search; wherein the search term specification means displaysvariation history for each of the search terms and when one of thehistory is selected, its search term is specified. In this way, theoperator can select a search term by referring to the search numbervariation history. The extraction is carried out using the search term.

5) The advertising medium determination device according to theinvention, further comprising: search term specification means forproviding a search term corresponding to the name of advertising objectto the extraction means while providing the name of advertising objectto the advertising medium data determination means when the name ofadvertising object and a search term corresponding thereto is provided.In this way, the extraction carried out using the provided search term.

6) The advertising medium determination device according to theinvention, further comprising: segment determination means for storing asegment determination rule for segmenting into the predetermined number,wherein the extraction means extracts the searcher's ID using thesegment determination rule provided from the segment determinationmeans. In this way, a searcher of each segment is specified according tothe segment determination rule.

7) The advertising medium determination device according to theinvention, further comprising: 1) search number variation historycalculation means for calculating variation history of search numberrepresenting chronological variation of the number of search for eachsearch term stored in the search term storage means; 2) search numbervariation history storage means for storing variation history of thenumber of search; and 3) segment determination means for determining asegment in accordance with a shape of the variation history of searchnumber; 4) wherein the extraction means extracts the searcher's ID usingthe segment provided from the segment determination means. In this way,a segment is determined in accordance with the shape of the variationhistory of search number.

8) The advertising medium determination device according to theinvention, wherein the segment determination means determines a segmentas a new segment when a variation ratio of the shape for the variationhistory of search number exceeds a predetermined ratio. In this way, asegment is automatically determined when a variation ratio for thevariation history of search number exceeds a predetermined ratio.

9) The advertising medium determination device according to theinvention, wherein the segment determination means displays thevariation history of search number and determines a segment using theprovided segment data. In this way, the operator can determine a segmentby referring to the displayed variation history of search number.

10) The advertising medium determination device according to theinvention, wherein the search term stored in the search term storagemeans is classified into categories, and the device further comprising:segment determination means for determining a segment under the segmentof the search term of a category to which the search term belongstherein. In this way, a segment is determined by the search termbelonging to the same category.

11) The advertising medium determination device according to theinvention, further comprising: search number variation historycalculation means for calculating variation history of search numberrepresenting chronological variation of the number of search for eachsearch term stored in the search term storage means; and search numbervariation history storage means for storing variation history of thenumber of search; wherein when a name of advertising object is input asan object to be corrected the search term specification means specifiesa search term that includes search number variation history similar tothe search number variation history of the inputted name of advertisingobject and provides the specified search term to the advertising mediumdata determination means as the term corresponding to the name ofadvertising object. In this way, change can be made with the search termincluding search number variation history similar to the search numbervariation history of the inputted name of advertising object.

12) The advertising medium determination device according to theinvention, further comprising: search number variation historycalculation means for calculating variation history of search numberrepresenting chronological variation of the number of search for eachsearch term stored in the search term storage means; and search numbervariation history storage means for storing variation history of thenumber of search; wherein when a name of advertising object is input asan object to be corrected the search term specification means specifiesa search term that includes search number variation history similar tothe search number variation history of the inputted name of advertisingobject, displays the search number variation history of the specifiedsearch term, and when any search term is selected, provides the selectedsearch term to the advertising medium data determination means as theterm corresponding to the name of advertising object. In this way, thechange can be made with the selected search term out of search termsincluding similar search number variation history.

13) The advertising medium determination device according to theinvention, wherein the search terms used as the search condition are aplurality of search terms combining one of logical AND and logical addor both of these, and wherein the extraction means calculates a timeframe from the beginning of search to the end of the search for eachsearch term and extracts searcher's ID belonging to each segment bycarrying out calculation based on the search condition. In this way, itis possible to extract searcher's ID belonging to each segment byperforming calculation based on the search condition of a plurality ofsearch terms.

14) The advertising medium determination device according to theinvention, wherein the calculation performed based on the searchcondition is a logical AND operation to be provided. In this way, it ispossible to extract searcher's ID by performing calculation based on alogical AND operation.

15) The advertising medium determination device according to theinvention, wherein a logical AND operation out of the calculations basedon the search condition calculates the maximum value of a period. Inthis way, the value that fulfills the search condition can be obtained.

16) The advertising medium determination device according to theinvention, wherein a logical AND operation out of the operations basedon the search condition calculates the average value of a period. Inthis way, calculation that fulfills the search condition can beperformed even when the search result against a partial conditiongreatly varies.

17) The advertising medium determination device according to theinvention, wherein the extraction means carries out the calculationafter normalization of the time frame about each of the obtained searchterms on a search term to search term basis. In this way, calculationcan be carried out with relative evaluation of periods for each ofsearch terms.

18) The advertising medium determination device according to theinvention, wherein the normalization is carried out through segmentationof the beginning of search to the end of the search for each search termin a predetermined number and through a logical AND operation dependingon to which segment the segmented frame belonging to. In this way, noseparate normalization processing is required.

19) The advertising medium determination device according to theinvention, wherein when data out of the normalized data of each of thesearch terms that is subject to logical AND operation differs from otherdata equal or more than a predetermined threshold value, a logical ANDoperation is carried out with ignoring such normalized data. In thisway, extraction can be carried out for searcher(s) who is even notsubject to the extraction without varying search condition because apart of search condition differs from other data equal or more than apredetermined threshold value.

20) The advertising medium determination device according to theinvention, wherein when no search timing exists in a search term that issubject to a logical AND operation, a logical AND operation is carriedout with ignoring of such search term if the number of such search isequal or less than a predetermined number. In this way, extraction canbe carried out for searcher(s) who is even not subject to the extractionwithout varying search condition because search result does not existfor a part of search condition.

21) The advertising medium determination device according to theinvention, wherein when no search timing exists in a search term that issubject to a logical AND operation, a logical AND operation is carriedout with ignoring of such search term if the number of such search isequal or less than a predetermined number. In this way, extraction canbe carried out for searcher(s) who is even not subject to the extractionwithout varying search condition because search result does not existfor a part of search condition.

22) The method of determining advertising medium according to thepresent invention, the method comprising the step of: storing within acomputer 1) information for specifying target attribution includinginformation for specifying information delivery medium of an object tocontact with correspondently with searchers' ID, and 2) data on a searchterm that corresponds a searcher's ID performing a search, a timing ofthe search, and the search term one another; wherein when a search termis provided, the computer extracts the timing of search for such searchterm from the search term storage means, segments the extracted searchtiming for each searcher's ID into a predetermined number inchronological order and extracts searcher's ID in each segment, andwherein the computer extracts a candidate of information delivery mediumfor the each segment from the extracted searcher's ID using the storedinformation for specifying target and determines one or more than tworepresentative candidate of information delivery medium from theextracted candidate of information delivery medium, thereby thecandidate of information delivery medium arranged in chronological orderof the each segment is determined as advertising medium data in the nameof advertising object provided correspondently to the search term.

In this way, it is possible to determine chronological order of theadvertising medium by segmenting each of the searchers for the searchtiming of search term in the past and by further referencing informationdelivery medium of an object to contact with by the searcher belongingto each of the segments.

23) The advertising medium determination device according to theinvention, comprising: 1) extraction means for extracting from searchterm storage means storing therein a searcher's ID, the timing ofsearch, and the term used for the search the timing of search for suchsearch term for each searcher's ID, segmenting the extracted searchtiming for each searcher's ID into a predetermined number inchronological order and extracting searcher's ID in each segment; and 2)advertising medium data determination means for extracting informationon candidate of information delivery medium for the each segment fromthe extracted each searcher's ID using information for specifying targetattribution including information for specifying information deliverymedium of an object to contact that is stored correspondently withsearchers' ID, determining one or more than two representativecandidates of information delivery medium from the extracted candidatesof information delivery medium, thereby determining the candidate ofinformation delivery medium arranged in chronological order of the eachsegment as advertising medium data in the name of advertising objectprovided correspondently to the search term.

In this way, it is possible to determine chronological order of theadvertising medium by segmenting each of the searchers for the searchtiming of search term in the past and by further referencing informationdelivery medium of an object to contact with by the searcher belongingto each of the segments.

24) The program for executing a computer the following steps accordingto the present invention, the program comprising the steps of: 1)extracting from search term storage means storing therein a searcher'sID, the timing of search, and the term used for the search the timing ofsearch for such search term for each searcher's ID, segmenting theextracted search timing for each searcher's ID into a predeterminednumber in chronological order and extracting searcher's ID in eachsegment; and 2) extracting information on candidate of informationdelivery medium for the each segment from the extracted each searcher'sID using information for specifying target attribution includinginformation for specifying information delivery medium of an object tocontact that is stored correspondently with searchers' ID, determiningone or more than two representative candidates of information deliverymedium from the extracted candidates of information delivery medium,thereby determining the candidate of information delivery mediumarranged in chronological order of the each segment as advertisingmedium data in the name of advertising object provided correspondentlyto the search term.

In this way, it is possible to determine chronological order of theadvertising medium by segmenting each of the searchers for the searchtiming of search term in the past and by further referencing informationdelivery medium of an object to contact with by the searcher belongingto each of the segments.

25) The method of determining advertising medium with computersaccording to the present invention, the method comprising the step of:storing within a first computer 1) information for specifying targetattribution including information for specifying information deliverymedium of an object to contact with correspondently with searchers' ID,and 2) data on a search term that corresponds a searcher's ID performinga search, a timing of the search, and the search term one another;wherein when a search term is provided, the second computer extractsfrom the first computer the timing of search for such search term,segments the extracted search timing for each searcher's ID into apredetermined number in chronological order and extracts searcher's IDin each segment, and wherein the second computer extracts from theextracted searcher's ID candidates of information delivery medium forthe each segment using the stored information for specifying target,determines one or more than two representative candidates of informationdelivery medium from the extracted candidates of information deliverymedium, thereby the candidate(s) of information delivery medium arrangedin chronological order of the each segment is determined as advertisingmedium data in the name of advertising object provided correspondentlyto the search term.

In this way, it is possible to determine chronological order of theadvertising medium by segmenting each of the searchers for the searchtiming of search term in the past and by further referencing informationdelivery medium of an object to contact with by the searcher belongingto each of the segments.

The term “information for specifying target attribution” in thisSpecification refers to information for specifying attributions astarget such as preference and belongings of each searcher. Theinformation further includes information for specifying informationdelivery medium.

The term “information for specifying information delivery medium” refersto information for specifying information delivery medium to which asearcher contacting with, the name of magazines as advertising mediumcorresponding thereto in the embodiments, other than that, the name ofnewspaper(s), TV program(s), site(s) on the Internet may be included aswell.

The term “extracts search timings of the search term(s) for eachsearcher's ID” refers to a process of extracting the earliest searchtiming for the searcher When plural searchers having the same search IDconduct plural searches. Here, the term “the earliest” refers to theoldest search timing when no starting timing of the search is specified,and the term means to the older search timing after the specified searchtiming when starting timing of the search is specified. For example,when three search timings such as 2008/1/10, 2008/2/16 and 2008/3/1exist for a search term and for a searcher X, such 2008/2/16 isextracted as the earliest search timing when starting timing of thesearch of 2008/1/15 is specified, and 2008/1/10 is extracted as theearliest search timing when starting timing of the search of 2008/1/15is not specified.

The term “data subject to logical AND operation differs from equal ormore than a predetermined threshold value” includes the case in which nosearch results exist and that are missing values.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a functional block diagram of an advertising mediumdetermination device 1 according to the present invention.

FIG. 1A is a functional block diagram of an advertising mediumdetermination device 200 according to an embodiment of the presentinvention.

FIG. 2 is an example of hardware structure of the advertising mediumdetermination device 1.

FIG. 3 is a diagram showing data structure of a search terms storagepart.

FIG. 4 is a diagram showing data structure of a target data storagepart.

FIG. 5 is a diagram showing an example of variation history data ofsearch number.

FIG. 6 is a diagram showing data structure of a created plan.

FIG. 7 is a diagram showing details of a created plan.

FIG. 8 is a flowchart of a process for determining advertising medium.

FIGS. 9A, 9B, and 9C are diagrams showing a dialog box to be displayed.

FIG. 10 is a flowchart of tabulation processing.

FIG. 11 is a display example of variation history data of search number.

FIG. 12 is a diagram showing data structure of variation history data ofsearch number for each segment.

FIG. 13 is a flowchart of plan creation processing.

FIG. 14 is a display example of advertising medium, which becomecandidates thereof.

FIG. 15 is a display example of advertising medium, which becomecandidates thereof.

FIG. 16 is an example of a dialog box to be displayed.

FIG. 17 is a display example of a determined advertising medium.

FIG. 18 is a flowchart of advertising medium correction processing.

FIG. 19 is an example of a dialog box to be displayed.

FIG. 20 is a data example of variation history data of search number.

FIG. 21 is a flowchart of a search term for correction determinationprocessing.

FIG. 22 is a diagram showing data structure of definition files.

FIG. 23 is an example of a dialog box for specifying a classification inwhich the name of advertisement object belongs.

FIG. 24 is an example of a dialog box for specifying a classification towhich the names of advertisement object belongs and a search term(s).

FIG. 25 is an example of a dialog box for determining search term forcorrecting plan(s).

FIG. 26 is a display example of pre-corrected variation history ofsearch number and post-corrected variation history of search number.

FIG. 27 is a display example of pre- and post-correction of plans.

FIG. 28 is a display example of pre- and post-correction of plans.

FIG. 29 is a flowchart of a process for specifying segments.

FIG. 30 is an example of variation history of the number of search.

FIG. 31 is an example of a dialog box for determining parameters forsegments of variation history of search number.

FIG. 32 is a diagram showing examples of calculation results of movingaverage values, total cumulative distribution numbers.

FIG. 33 is a display example at automatic segment processing.

FIG. 34 is another display example at automatic segment processing.

FIG. 35 is a diagram illustrating status displaying segment candidateson variation history of search number.

FIG. 36 is a functional block diagram of a questionnaire resultanalysis-supporting device 100.

FIG. 37 is an example of hardware structure of the questionnaire resultanalysis-supporting device 100.

FIGS. 38A and 38B is diagrams showing data structure of a search termstorage part.

FIG. 39 is a diagram showing data structure of a questionnaire resultsdata storage part.

FIG. 40 is a diagram illustrating an example of variation history ofsearch number.

FIG. 41 is a flowchart of analysis processing.

FIG. 42 is an example of a dialog box to be displayed.

FIG. 43 is a flowchart of tabulation processing.

FIG. 44 is a display example of variation history of search number.

FIG. 45 is a diagram illustrating data structure of variation history ofsearch number for each segment.

FIGS. 46 and 46 b are examples of cross tabulation results.

FIG. 47 is an example of cross tabulation results a part of which ishighlighted.

FIG. 48 is an example of highlighted cross tabulation result.

FIG. 49 is an example of an image into which conditions for carrying outcross tabulation processing.

FIGS. 50A and 50B are examples of results in the order of significantitems.

FIG. 51 is an example of results in the order of significant item.

DESCRIPTION OF REFERENCE NUMERALS

-   -   1: Advertising medium determination device    -   23: CPU    -   27: Memory

EMBODIMENTS FOR CARRYING OUT THE INVENTION 1. Outline of the OverallStructure

FIG. 1 shows a functional block diagram of an advertising mediumdetermination device 1 according to the present invention. Theadvertising medium determination device 1 comprises target specifyinginformation storage means 2, search term storage means 3, extractionmeans 4, advertising medium data determination means 5, search termsspecifying means 6, search number variation history calculation means 7and search number variation history storage means 8.

The target specifying information storage means 2 stores information forspecifying target attribution including information for specifyinginformation delivery medium of an object to contact with correspondentlywith searchers' ID. The search term storage means 3 correspondentlystores a searcher's ID, the timing of search, and the term used for thesearch. When a search term is provided as a search condition, theextraction means 4 extracts the timing of search for such search termfor each searcher's ID from the search term storage means, segments theextracted search timing for each searcher's ID into a predeterminednumber in chronological order and then extracts searcher's ID belongingto each segment.

The advertising medium data determination means 5 extracts informationon candidate of information delivery medium for the each segment fromthe extracted each searcher's ID using information for specifying atarget stored in the target specifying information storage means 2,determines one or more than two candidate(s) of information deliverymedium from the extracted candidate of information delivery medium,thereby the candidate(s) of information delivery medium arranged inchronological order of the each segment is determined as advertisingmedium data in the name of advertising object provided correspondentlyto the search term. The determined advertising medium data is stored inresult storage means 9.

In response to providing the name of advertising object and a searchterm corresponding thereto, the search terms specifying means 6 providesto the extraction means 4 a search term corresponding to the name ofadvertising object while providing the name of advertisement object theadvertising medium data determination means 5.

The search number variation history calculation means 7 calculatesvariation history of search number representing chronological variationof the number of search(es) (the term “the number of search” ishereinafter referred to as “search number” or equivalent term) for eachsearch term stored in the search term storage means 3. The search numbervariation history storage means 8 stores the calculated variationhistory of search number. In addition, when a name of advertising objectis input as an object to be corrected, the search terms specifying means6 specifies a search term including variation history of search numbersimilar to the variation history of search number of the name ofadvertising object being inputted, displays the variation history ofsearch number to be specified and any term is selected, the selectedterm is provided to the advertising medium data determination means 5 asa term corresponding to the name of advertising object.

The extraction means 4 calculates a time frame from the beginning ofsearch to the end of the search for each search term when a plurality ofsearch terms, combining one of logical AND and logical add or both ofthem, are provided as a search condition, and extracts searcher's ID foreach segment by carrying out calculation based on the search condition.

Further, segment determination means 11 determines segments inaccordance with the shape of the variation history of search number. Theextraction means 4 extracts the searcher's ID using the segmentsprovided from the segment determination means 11.

Although, an example of storing the target specifying informationstorage means 2 and the search term storage means 3 within oneadvertising medium determination device 1, both may be stored in aseparate computer and can also be read therefrom.

2. Hardware Structure

Hardware structure of the advertising medium determination device 1 willbe described. FIG. 2 is an example of hardware structure of theadvertising medium determination device 1 using a CPU.

The advertising medium determination device 1 comprises a CPU 23, amemory 27, a hard disk 26, a monitor 30, an optical drive 25, a mouse28, a keyboard 31 and a bus line 29. The CPU 23 controls each of theparts according to each of programs stored in the hard disk 26 throughthe bus line 29.

The hard disk 26 comprises an operating system program 26 o (hereinafterreferred to as OS for short), an advertising medium determinationprogram 26 p, a search term storage part 26 k, a target data storagepart 26 t, a search number variation history storage part 26 h and anadvertising medium determination data storage part 26 b.

In the search term storage part 26 k, user IDs and the search timingsare stored as searchers' IDs who conduct searches for each search termas shown in FIG. 3. In this embodiment, date of search and their timeare stored as the search timings, instead of that, date of search alonemay be stored. Such search timings and users' IDs for each search termmay store the search term and its search timing for the searches usingsearch engines on the Internet for each user targeting the users whologin a portal site for example.

As shown in FIG. 4, target attribution specifying information containingadvertising medium specifying information for specifying advertisingmedium to which user him/her-self contact is stored in the target datastorage part 26 t for each user. For example, a user having a userID10001 has contacting medium such as magazine B, TV programs A, B asadvertising medium and target attribution of the user such as “tend topay attention on dress-up”, “sensitive to the fashion” is storedtherein. Further, products that is having by the user (for example,“computer A”, “drink A”) are stored therein. As to information onproducts, data such as purchasing history, purchasing plan andpurchasing quantity and so on may be handled. Such target attributionfor each user may be acquired one of at the new registration of the useror through a questionnaire and the like thereafter.

As will be described later, “date and hour”, “number of searchrespondent”, “respondents'IDs” for each search term are stored in thesearch number variation history storage part 26 h as variation historyof search number representing chronological variation of search numberby tabulating each of search terms stored in the search term storagepart 26 k. For example, for a search term shown in FIG. 5, one search isconducted on 2007/4/2 by one searcher having ID of “10011”. In addition,three searches are conducted on 2007/4/5 by three searchers having ID of“120303”, “10013” and “10024”. Thus, variation history of search numberin chronological order is recorded in the search number variationhistory storage part 26 h.

As shown in FIG. 6, advertising medium determination data generated bythe advertising medium determination program 26 p that will be describedlater is stored in the advertising medium determination data storagepart 26 b. FIG. 7 shows tangible data structure of each advertisingmedium determination data. As illustrated in the drawing, within theadvertising medium determination data, an advertising media is assignedto each of advertising periods.

The advertising medium determination program 26 p generates advertisingmedium determination data illustrated in FIGS. 6 and 7 by carrying outtabulation processing (step S2), segment determination processing (stepS3) and plan creation processing (step S5) shown in FIG. 8. The detailsof these processing will be described later.

In this embodiment, Windows Vista (a registered trademark or atrademark) is employed as an operating system program (OS) 26 o, anyother OS may also be used as well.

Each of the programs is read out from a CD-ROM 25 a storing programs viathe optical drive 25, and such program is installed into the hard disk26. Alternatively, each of the programs can read out from a computerreadable medium other than CD-ROM, such as flexible disks (FD), IC cardsand so on and is installed into the hard disk. In addition, such programmay also download through a communication line.

In this embodiment, the computer indirectly performs programs stored inthe CD-ROM by installing the programs from the CD-ROM into the hard disk26. However, it is possible to perform the programs stored in the CD-ROMdirectly from the optical drive 25 without any limitation of theabove-described way. Computer implementable programs include not onlyprograms capable of being directly performed by just installing them,but they also include the programs need to be converted into otherformats and the like (for example, that need to be decompressed fromdata compression format and the like), in addition to program(s) thatcan be performed in combination with other module parts.

3. Advertising Medium Determination Processing

In what follows, advertising medium determination processing will bedescribed with reference to FIG. 8. the cpu 23 carries out inputprocessing for the name of advertising object, history utilizing searchterm and the beginning period of campaign (step s1). such processing maybe carried out by displaying a dialog box shown in FIG. 9 and promptingthe input therein. in FIG. 9 a, the name of advertising object is set-upby inputting the name in a region 31 and clicking a button 32. in FIG. 9b, the name of advertising object is set-up by inputting a search termin a region 33 and clicking a button 34. in FIG. 9 c, the beginningperiod of campaign may be input in regions 35 to 37. in the belowexample, it is assumed that “shampoo x”, “tsubaki” and “May 1, 2008” arerespectively input therein as a name of advertising object, a searchterm utilizing history and a beginning period of campaign.

1) [Tabulation Processing]

The CPU 23 carries out tabulation processing (FIG. 8, step S1). Thedetail of tabulation processing is shown in FIG. 10.

The CPU 23 judges whether a search term utilizing history (hereinafterreferred to as search term) is input (FIG. 10 step S11), all the recordof search for the search term is extracted when the search term in input(step S13). In this case, the CPU 23 extracts a searcher ID “10011”,search date and hour “06:01 on 2007/4/2”, a search term “TSUBAKI”, asearcher ID “12303”, search date and hour “16:22 on 2007/4/5”, a searchterm “TSUBAKI”, a searcher ID “10013”, search date and hour “16:24 on2007/4/5”, a search term “TSUBAKI”, a searcher ID “10024”, search dateand hour “19:10 on 2007/4/5”, a search term “TSUBAKI” and so on becausethe search term for this case is “TSUBAKI”.

The CPU 23 specifies the earliest searched record within the extractedrecords (step S15). Then the CPU 23 sets the date and hour for theearliest search timing as a search date and hour of population for thesearch term (step S17). For example, in the case shown in FIG. 3, thesearch date and hour of population for the search term “TSUBAKI” becomes06:01 on 2007/4/2.

Depending on the search term being input at step S11, the search dateand hour of population therefor could be far in advance. In that case,it is possible for an operator to input arbitrary date and hour bydisplaying the search date and hour of population calculated at step S7on the monitor and ask for him/her to confirmation “search date and hourof population is a certain yy/mm/dd, is it OK?”.

The CPU 23 calculates individual search timing difference by extractingthe earliest period of record after the search date and hour ofpopulation for each ID of the extracted record and records thecalculated differences (FIG. 10 step S19). In this embodiment, days areused as individual search timing differences. However, in the case ofFIG. 3, the search date and hour 2007/4/2, respondent number “1”,searcher's ID “10011”, the search date and hour 2007/4/5, respondentnumber “3”, searchers' IDs “12303”, “10013” and “10024” and so on shownin FIG. 5 can be obtained as the number of respondents of searches perday and respondents' IDs. The unit for tabulation may be inputarbitrarily such as a week, a month or morning, afternoon, a certainperiod (for example three hours).

When plural searches for the same search term(s) are conducted, theearliest date thereof is the earliest search date and time for the userand the difference between the earliest search date and time and thesearch date and hour of population becomes an individual search timingdifference for the user.

2) [Segment Determination Processing]

Upon completion of the tabulation processing, the cpu 23 carries outsegment determination processing (FIG. 8 step s3). in this embodiment,the steps of displaying variation history of search number for thesearch term by which the above variation history data of search numberis generated, chronologically segmenting such data into a predeterminednumber using the search timing as a key with reference to the variationhistory by the operator, segmenting from the beginning of the search tothe end thereof for the search term into a predetermined number, andextracting user ids that belong to each of the segments. such processingwill be described herein.

The CPU 23 displays line charts in accordance with the above variationhistory data of search number. In this embodiment, such line chartstakes the abscissa axis and the ordinate axis respectively as dates(individual search timing differences) and the number of searches.Consequently, a tabulation segment distribution shown in FIG. 11 isdisplayed. The operator designates a method of segmentation and thenumber of segments with reference to such distribution. In this way, thenumber of segments is determined. In description below, it is assumedthat the number of segments five is designated under the segmentationbased on quantile. The segmentation based on quantile is a segmentationin which total search number is equally segmented into a predeterminedsegment number. In this case, the total number is segmented into five bydividing until each of the total reaching to 20% of the total becausethe number of segment is five. An example of post-segmentation data isshown in FIG. 12.

For the method of segmentation, various methods such as The innovationadoption curve of Rogers and so on other than the quantile may also beemployed. In addition, segmentation in calendar such as monthly and timesegment starting at search date and hour of population and so on may beused.

3) [Plan Creation Processing]

Subsequently the CPU 23 carries out plan creation processing (FIG. 8step S5). in the plan creation processing, a user belonging to thesegment obtained by step S3 is specified, and candidate of informationdelivery medium for the each segment is extracted using information forspecifying target. further, one or more than two representativecandidates of information delivery medium are determined from theextracted candidate of information delivery medium, thereby therepresentative candidates of information delivery medium arranged inchronological order of the each segment are determined as advertisingmedium data in provided in response to the search term.

In description below, plan creation processing will be described withreference to FIG. 13. The CPU 23 displays variation history data ofsearch number (step S21). Then the CPU 23 reads out the number ofsegment “5” (FIG. 13 step S23). The CPU 23 initializes segment to beprocessed j (step S25), extracts all the user IDs belonging to the jthsegment and extracts the advertising media from its target attributionand calculates a ratio thereof within the segment (step S27). In thiscase, because of j=1, all the user IDs that belong to the first segmentC1 is read out from the variation history data of search number shown inFIG. 5, all the advertising media to which each user frequently contactsare read out, the number of the advertising media is counted and thecontact frequency ratio to the medium in the segment may be calculated.For example, if the numbers of users belong to segment C1 are 1000 and arecord is made that the numbers of these users who frequently contact tomagazine A are 123, the contact frequency ratio to the magazine A is12.3%. In this way, the contact frequency ratio within the segment iscalculated for the entire advertising medium.

The CPU 23 judges whether or not all of the segments have been processed(step S29), in this case, it increments the segment to be processed jbecause not all of the segments have been processed (step S30) andrepeats steps subsequent to step S27.

Upon completion of processing for all the segments, the results aretabulated (step S31). Further, the CPU 23 determines advertising mediumthat become candidate(s) of advertisement medium and displays them (stepS33). A display example thereof is shown in FIG. 14.

In this embodiment, the advertising medium is listed in the order ofones having the higher contact frequency ratio within the segment, andwithin the listed mediums, the mediums having their contact frequencyratio higher than a predetermined value in the segment are specified ascandidates and highlight them for particular display. However, the oneshaving the highest contact frequency ratio may be determined ascandidates without restriction of the above way. Further, the particulardisplay may be a display in other color(s) and a display at some otherplace from other media, a display with different character size(s) andother display variations. Such particular display is an arbitrarydesignation.

If the user want to change the display upon taking a look at thedisplayed candidates, he/she may just select a selection region of theadvertising medium with a pointing device. For example, in FIG. 14, themedium having more than 3% higher contact frequency ratio are shown in aparticular display as candidates. No highlight display is made on themagazines K and M because these magazines do not have more than 3%higher contact frequency ratio than the total average contact frequencywithin a segment C4. Similar fact is applied to the magazines K and Mwithin a segment C5. Regions 53, 54, 55 and 56 may be clicked when theoperator selects these advertising media.

The CPU 23 judges existence of a command for change (step S36) andchanges the display when it judges that such command exists (step S37).FIG. 15 shows a display state after the display of candidates haschanged while the regions 53, 54, 55 and 56 are in clicked state.

By varying the values in the region 61, threshold values displayed inhighlight display by default can be changed.

The operator selects a button 51 illustrated in FIG. 15 when it issatisfactory. The CPU 23 judges whether the button 51 is clicked afterstep S37 (FIG. 13 step S35) and stores the plan as a determined planwhen the button 51 is clicked. The name of a plan may be input throughthe steps of displaying an image shown in FIG. 16 for prompting input ofthe plan into a region 57 and clicking a button 58.

FIG. 17 shows outline of the determined plan A.

In this embodiment, an example of selecting magazines as advertisingmedia, other advertising medium such as news papers, televisions, theInternet and so on can also be selected.

In this embodiment, suggestions for advertising medium plan are createdby carrying out the steps of adequately segmenting search timing for asearch term(s) using the search results at search engines on theInternet, determining respondents that belong to the segment andextracting the advertising medium to which the respondent(s) frequentlycontacting with. In this way, suggestions for advertising medium plancorresponding to a past search tendency can be created. It is consideredthat the degree of interest for a particular search term(s) has acertain relation to the interest to new products. Suggestions foradvertising medium plan that is free from user's subjective can becreated because search timings for particular search term(s) haverelevance with the sensitivity to trends. In this embodiment, actualnumber of days for conducting search is used as the days for eachsegment, but it is not limited to that way.

4. Correction Processing

A “plan A” of “shampoo X” thus created is a suggestion of plan that iscreated on the absolute assumption that the product gets attentionsimilar to a search term previously searched. A new search is conductedfor the name of this advertising object “shampoo X” as a new searchterm. Consequently, there might be a possibility that the search resultthereof is entirely different from that of the search term “TSUBAKI”. Inthis embodiment, a created suggestion of plan is correctedcorrespondently with actual search history in addition to use searchhistory of another search term. In this way, a suggestion foradvertising medium plan corresponding to the actual search history forthe name of advertising object may be created.

In the below description, the case where a correction being made on 6/19about a “plan A” for “shampoo X” that is created under the name ofadvertising object using “TSUBAKI” with another search term, will bedescribed.

The CPU 23 carries out input processing of a correction object (stepS41). To do that, prompt the input by displaying a dialog box shown inFIG. 19. The operator inputs “shampoo X” in a region 61. The CPU 23displays the plan on shampoo X on a region 63. In this case, the plan Ais displayed on the region 63 since the “plan A” exists.

The operator clicks a determination button 65 when the correction objectis plan A. By doing that, the input processing is completed. Pluralplans are displayed on the region 63 because there might a case whereplural plans are stored for one advertising object name.

Subsequently, the CPU 23 carries out tabulation of search history usingthe search result stored in a search term storage part wherein thesearch history is made using the search term “shampoo X” (FIG. 18 stepS43). Detailed description of such tabulation processing because suchdescription is similar to that of step S2 in FIG. 8. In this way, searchresults from 5/1 to 6/19 for the search term “shampoo X” illustrated inFIG. 20 is obtained.

The CPU 23 determines a search term having a similar variation historyof search number to the search term “shampoo X” using therewith as asearch term for correction using search history on the search term“shampoo X” (step S45). The details of step S45 will de described withreference to FIG. 21.

The CPU 23 carries out a range specifying processing (step S51). In thisembodiment, as shown in FIG. 22, definition files defining hierarchicstructure in which small classifications belonging thereto and largeclassifications to which the small classifications belonging for eachsearch term are stored in the hardware 26 (see FIG. 2) and specifieswhich range of search terms is judged for similarities. In thisembodiment, the operator can specify the range by displaying a dialogbox shown in FIG. 23. Once a category is determined, the operator mayselect a determination button 71. In the case of performing judgment forsimilarity of partial search terms within the small classifications, letthe operator to select by displaying a dialog box shown in FIG. 24. Whena button 74 is selected for the search terms displayed on a region 73,the terms are displayed on a region 75. Upon completion of all theselections, the operator clicks on a button 76. In this case, it isassumed that shampoos Y1, Y5 and Y6 are selected.

The CPU 23 carries out tabulation processing and search historycalculation processing for the search terms of the specified range (FIG.21 step S53). Detailed descriptions of the tabulation processing andsearch history calculation processing are omitted because these aresimilar to the above-described ones. In this way, variation history ofsearch number for the shampoos Y1, Y5 and Y6 is obtained.

The CPU 23 calculates similarity between 50 days search history of thesearch term “shampoo X” from 5/1 to 6/19 and the variation history ofsearch number for the shampoos Y1, Y5 and Y6 at the first 50 days anddisplays a list of the search terms and the similarity (FIG. 21 stepS55). FIG. 25 shows such list the search terms and the similarity.

In this embodiment, although both coefficients of correlation of twovariation history of searches are used as a method of calculatingsimilarity, any other methods that can judge similarity of line chartsuch Euclidean distance or square sum and so on may also be usedtherefore. Further, plural calculation methods may be combined as well.

In this case, the operator selects the shampoo Y6 as a search term forcorrecting “plan A” related to “shampoo X” and clicks the determinationbutton because the similarity of the shampoo Y6 has a relative highvalue such as 0.88. The CPU 23 judges whether the determination buttonis clicked (step S57), displays the pre-correction variation history ofsearch number and the post-correction variation history of search numberin a superimposed manner. An example of such display is shown in FIG.26.

Upon completion of step S45 of FIG. 18, the plan A is corrected with thedetermined search term (step S47). Detailed description of suchprocessing is omitted because these are similar to steps S3 and S5 ofFIG. 8. No complete match for the number of segments at pre-andpost-correction is obtained in step S3 of FIG. 8. Partial segments havealready been completed by running actual advertisements. Therefore,additional correction(s) is made on the plan(s) created after thecorrected plan(s) as well.

In general, advertisement contract signs up with medium providers for acertain period. Therefore, there might be a case that no correction forthe contract that has already been ordered is accepted evenadvertisement plan itself is changed. For example, a correction has madeon 2008/6/19 in this example, but determination has made that themagazine C will be the advertising media until 2008/6/30 for the segmentC2 and the fact has already notified to the magazine C. Therefore, theorder can not be cancelled. Running advertisement of multiple medium isperformed for a part of advertising period in this embodiment, becausedesirable effect may be expected for performing a correction at an earlystage thereof. In this embodiment, magazines H and C are determined asadvertising medium from 6/20 to 7/30. Consequently, advertising mediaoverlap from 6/20 to 6/30. Further, segments after 6/20 are defined twosegments.

FIG. 27 shows an example of a list of plans at pre-and post-correctionstage and FIG. 28 shows an example of summarized plans thereof. Both C2and C2′ may be displayed in a summarized manner in FIG. 28.

In this way, more realistic plans can be created by correcting the nameof advertising object with the search term(s) having similar searchhistory using actual search history(ies).

5. Specific Processing for Search Term

In the above-described embodiments, it is necessary for the operator tospecify which search term(s) is to use for creating initial plan(s). Itis sometimes difficult to do such term specification appropriately evenfor a well-experienced operator. To solve such a problem, it is possibleto classify search term(s) by category and may select a search term thatbelongs to the same classification. Specifically, definitions filesshown in FIG. 22 are stored and the operator to specify one ofclassification and search term by displaying the dialog boxes shown inFIGS. 23 and 24.

In addition, a search term for creating a plan may be specified by theoperator from variation history of search number by calculating thevariation history upon selecting an arbitrary search term and bydisplaying the history.

6. Specification of Segments

In this embodiment, the operator specifies the number of segment. On theother hand, candidates for the segment may also be determinedautomatically by a computer. Details of automatic determinationprocessing will be described with reference to FIG. 29. In this process,it is defined as one segment when one of the cases in which the numberof search history increases and decreases.

The CPU 23 reads in object data to be processed (FIG. 29 step S71).Here, it is assumed that variation history of search number shown inFIG. 30 is provided. The CPU 23 carries out a specific processing on aconditional setup for tabulation unit, rising points and dropping pointsand a calculation method for the provided number of search history (stepS72). In this embodiment, it makes the operator to input adequate databy displaying a dialog box shown in FIG. 31. In this example, thetabulation unit and the conditional setup for rising points have beenset up respectively as “week”, “three consecutive weeks” and “total riseof equal or more than 0.5%”. Another conditional set-up for movingaverage “exists” AND “average of previous-four weeks”. The same asapplied for the dropping points.

Then the CPU 23 calculates moving average deviations and cumulativedistributions (step S73). FIG. 32 shows the calculation results thereof.

The CPU 23 extracts candidates of rising points and that of droppingpoints (step S74). In this case, such candidates were extracted whereone of raising and dropping of equal or more than 192 people inconsecutive three weeks because the number of cumulative searchers is38412 people and it is required that the rise and drop of equal or morethan 0.5% for overall cumulative distributions continue more thanconsecutive three weeks. In this case, week 10 to week 16 and week 22 toweek 25, and, week 17 to week 21 and week 26 to week 28 respectivelyextracted as candidates for rising points that for dropping points.

The CPU 23 excludes the last candidate of rise from the candidates whenrise point candidates consecutively exist out of the extractedcandidates in step S74 until no consecutive candidates exist and itexcludes the first candidate of drop from the candidates when rise pointcandidates consecutively exist until no consecutive candidates exist(step S75). Consequently, week 11 to week 15, week 21 to week 25, week17 to week 20 and week 26 to week 27 are excluded.

The CPU 23 defines a rising point(s) and a dropping point(s)respectively when no rise point candidates consecutively exist and droppoint candidates consecutively exist (step S76). In this case, week 10and week 22, and week 21 and week 28 are respectively defined as risingpoints and dropping points.

The CPU 23 displays time frames between each of such points (the risingpoints or the dropping points) and the number of search thereof (stepS77). In this case, a total of five rising points and dropping pointsare defined and intervals C1 to C4 shown in FIG. 33 and such intervalsare displayed in the above five points.

The operator carries out specific processing for rising points anddropping points with reference to such display (step S78). Specifically,an option, in which time frame is incorporated with its vicinity if theperiod is too short, may be carried out. In this case, the interval C3is incorporated with the interval C4 locating behind it because theinterval C3 is week 21 alone and the search ratio thereof is a low valueof 0.1%. FIG. 34 shows a display example of the post-incorporation. Inthis way, the operator can exclude the segment(s) having less searchnumber.

Then, the CPU 23 displays the periods and the number of search for eachsegment with the specified rising point(s) and the dropping point(s)(FIG. 29 step S79). FIG. 35 shows a display example thereof.

Although a list of values are displayed and correction there isperformed in this embodiment, it is possible to carry out the specificprocessing in step S78 by displaying both a line chart and boundarylines and adding and deleting the boundary lines. Further, both of theabove may also be displayed.

Hence, the boundary of segments can automatically be determined from theshape of variation history of search number. In this way, even anoperator unfamiliar with segmentation of the variation history of searchnumber cam defines the segments in response to the shape of thevariation history of search number.

In the above-described embodiments, candidates are displayed, suchcandidates may automatically be determined

Further, boundary lines for segmenting segments are defined using amoving average of the variation history of search number in thisembodiment. Consequently, it is possible to carry out exclusion of week2 having a short-term rise and detection of a rising trend includingweek 11 having a short-term drop.

7. Specification of Plural Search Terms

In the above embodiments, examples of specifying just one search termhave been described, search terms defining to perform calculation oflogical sum (or) and/or logical and (and) for plurality of search termscan be provided.

For example, if “a search term A AND (a search term B OR a search termC) is provided, an ID that fulfill such conditions may be extracted asit is. Specifically, conduct a search for one of the search terms B andC, and extract a searcher who conducts a search for the search term A aswell as the search terms B and C. Each ID uses “the date conducting asearch for one of the search terms B and C and searching the search termA” for the evaluation to the searcher. The earliest date for “conductinga search for one of the search terms B and C and searching the searchterm A” out of all the IDs may define as a population search date.

Such search conditions are effective in the case of needs for extractingand segmenting searcher(s) who conduct a search for plural search termsat the same period of time.

In addition, as to time difference for search, individual search timingdifference is calculated for each search term and then that may becalculated in response conditions therefore. In this case, ANDrequirement calculates the maximum value and OR requirement calculatesthe minimum value. For example, individual search timing difference isMAX [10 days later, MIN (20 days later, 30 days later)]=20 days laterwhen individual search timing difference is set at 10 days later fromthe population search date for the search term A, 20 days later from thepopulation search date for the search term B and 30 days later from thepopulation search date for the search term C.

Segment of individual search timing difference may be calculated foreach of search terms for each search term and then that may becalculated in response conditions therefore. For example, individualsearch timing difference is segmented so that each having approximatelyfive minutes (in the order C1 to C5, so as to arrange the terms inshorter period appears first). When segmentation is carried out as thesearch term A: C1, the search term B: C1 and the search term C: C2,individual search timing difference becomes MAX [1, MIN (1, 2)]=1 andsegment of individual search timing difference comes to C1.

Such technique is effective in the case of needs for detecting andsegmenting searcher(s) who conduct a search for plural search termsbelonging to the same category at consistently early stage.

Hence, comprehensive evaluation of variation history of search numberfor each search term can be performed relatively by normalizing thesearch timing for plural search terms. Alternatively, the technique forthe normalization is not limited to the above way such as classifying insegments, but an ordinary technique(s) for normalization may also beemployed.

When the search condition is defined for carrying out a logical ANDcalculation for plural search terms, there might be cases in which nosearch result exists therein or obtaining search result greatly differfrom other result if the result does exist therein. In that case, it ispossible to evaluate in the above way, but the evaluation can also beperformed under a partially eased condition as described below.

For example, the following causes are considered for the reason whythere are no search results for a certain search term out of the searchterms specified for carrying out logical AND calculation. One of thecauses is lower sensitivity of the user to the search term. Anothercause is not relative to the sensitivity to the information such as thecases that one of no search is carried out due to already known searchterm and due to accidentally no interesting on such search term. It isnot necessary for the user to extract the search term if he/she haslower sensitivity on the term, but for the latter case, the termpreferably be extracted. Extraction may be carried out for such user inthe following way.

In what follows, the case in which segment of individual search timingdifference is calculated for each search term will be described. Forexample, it is assumed that search terms “search term W1 AND search termW2 AND search term W3 AND search term W4 AND search term W5” areprovided and the following search results are obtained.

UseR U1: search term W1 to search term W5: all the terms belong tosegment C1

User u2: search term w1 to search term w5: all the terms belong tosegment c5

User U3: search term W1 to search term W4: all the terms belong tosegment C1, search term W5: the term belong to segment C5.

Hence, for evaluation, judgment using the maximum values, minimumvalues, average values, mode values and threshold values (for example,if more than a predetermined number belonging to a certain segment, itis judged that the search term is recognized as such segment) can beperformed, if the search term W1 to search term W4 belong to segment C4,but the rest belongs to another search term W5, like the user U3.

The following calculation technique is feasible, specially when nosearch result exists for a part of the search terms to which logical ANDcalculation is imposed, for example, in the case of conducting actualsearch for the search terms W1 and W2 by a user but no actual search forthe search term W3.

1) The IDs satisfying all the conditions are extracted. In other words,any IDs having any deficit are eliminated.

2) Individual search timing difference is calculated for each searchterm and then that is calculated in response conditions therefore. Forexample, it is assumed that individual search timing difference of aperson i for a search term j is defined as NA when any deficit valueexist and defined as search time (ij) when no deficit value exist.During the calculation of data containing any deficit value as anobject, AND condition and AVERAGE condition are defined as NA and ORcondition is set to the minimum value (NA, if all the values are NA). Onthe contrary, during the calculation of data not containing deficitvalue as out of the object, AND condition is set to the maximum valueexcept for NA (NA, if all the values are NA), AVERAGE condition isdefined to the average value except for NA (NA, if all the values areNA) and OR condition is set to the minimum value except for NA (NA, ifall the values are NA). Segmentation of time difference is carried outsimilar to the case of selecting one search term subject to setting thesegment of individual search timing difference using T (i) to be definedas individual search timing difference that is calculated in response toconditions.

3) Segmentation of individual search timing differences is calculatedfor each search term and then that is defined in response conditionstherefore. In the above 2), the calculation is carried out withdifference in days, but this calculation method differ from the above inthat segments are obtained and the calculation is carried out with suchsegments. Specifically, a method of segmentation is set and the segmentof individual search timing differences of a person i for a search termj is defined as NA when any deficit value exist and defined as segmentof search time difference c(ij) for each search term when no deficitvalue exist. As to i, positive integers such as 1, 2, 3 so on areprovided at early segments and calculation is carried out provided thatC(i) equals to i. During the calculation of data containing any deficitvalue as an object, AND condition and AVERAGE condition are defined asNA and OR condition is set to the minimum value (NA, if all the valuesare NA). On the other hand, during the calculation of data notcontaining deficit value as out of the object, AND condition is set tothe maximum value except for NA (NA, if all the values are NA), AVERAGEcondition is defined to the average value except for NA (NA, if all thevalues are NA) and make it to a positive integer by performing round offthereof. OR condition is set to the minimum value except for NA (NA, ifall the values are NA). Tabulation may be carried out using C (i) to bedefined as segment of individual search timing differences that iscalculated in response to conditions.

8. Other Embodiments

In this embodiment, the case, where the search results using searchengines on the internet have already been stored, has been described,but in the case of performing the correction processing the searchresults until starting such processing may be stored.

In this embodiment, the case where information for specifying targetattribution and data on search term are stored in the advertising mediumdetermination device has been described as an example, it is possible toconfigure such that one of these data or both data is stored in anothercomputer (for example, a center server) and reads out such data througha network.

For acquiring search results, it is possible to configure such thatinstallation of a program for storing history of using search engineswithin the user's PC is required during the user registration, storingsearch term(s) and search at each search and send them to the centerserver regularly or irregularly. In this way, well-known technique canbe employed for the method of collecting search results.

In the above described embodiment, the operator inputs the searchterm(s), the search term(s) belonging to a certain categorycorresponding to the name of advertising object can automatically bedetermined by storing search term(s) that is classified into categories.Further, they may be displayed as candidates and can be selected one ofthese.

Search term(s) may be specified by carrying out steps of storingvariation history of search number for each search term and displayingthe histories to the operator and asking for selecting one of thehistories.

Segment may be determined using a segment determination rule(s) forsegmenting into a predetermined number, wherein the segmentdetermination rule(s) is stored.

The segment may be determined using segment of search term for categoryto which a search term(s) belong, wherein the search term(s) classifiedinto category is stored.

The search terms specifying means may automatically specify a searchterm(s) including the variation history of search number similar to thatof the name of advertising object being inputted when the name ofadvertising object is input as an object for correction. In addition,instead of automatic specification, it is possible to provide theselected search term(s) to the advertising medium data determinationmeans as a word to the name of advertising object.

In this embodiment, days are used for basis of various time frames, butweek, month, or even morning, afternoon, hours (for example, three hourbasis) and so on may arbitrarily be applied.

Also, segment is specified in the form of mm/dd-to-mm/dd, but it ispossible to specify segment relatively in a relative period such as onemonth later from a certain date.

As to tabulation segment, arbitrarily time intervals such as one monthand so on may be set. Further, search date and hour of population mayalso be set arbitrarily. For example, monthly tabulation will be carriedout by setting the population search date arbitrarily as January 1 andthe tabulation segment in one month. This enable to correspondence to asegment in a calendar-form.

In the above-described embodiments, the candidate(s) is determined atthe step S33 in FIG. 13, such candidate(s) may also be determined with avalue considering advertisement cost(s). Specifically, such candidatesmay be arranged in the order of having higher medium contact ratio perunit cost (the value obtained by dividing the contact rate by anadvertisement cost). For example, as shown in FIG. 14, the contact ratioof magazine A is 12.3%, that of magazine B is 10.5% that of magazine Cis 7.5%, that of magazine D is 4.5% and that of magazine E is 2.5%respectively. In this case, the contact ratio per unit costs become 0.12for the magazine A, 0.15 for the magazine B, 1.0 for the magazine C,0.075 for the magazine D, 0.083 for magazine E when the advertisementcosts are stored as a million yen for the magazine A, 0.70 million yenfor the magazine B, 0.75 million yen for the magazine C, 0.60 millionyen for the magazine D and 0.30 million yen for the magazine E. Theseare arranged in the order of the magazine B, the magazine A, themagazine C, the magazine E and the magazine D when the magazines arearranged in descending order.

Alternatively, advertisement cost per unit medium contact ratio (thevalue obtained by dividing an advertisement cost by the contact rate) iscalculated and the candidates may be arranged in ascending order.

Further, candidates may also be determined with content rate. Thecontent rate is a rate in each segment in the case of paying attentionon a specific advertising medium. For example, the content rate of asegment C1 for the magazine E becomes 850 divided by 1000 equals to 0.85when the number of users who belong to each of the segments C1, C2, C3and C4 is 850, 100, 20 and 30 respectively in the case of existing 1000users in the entire segments who memorize the magazine E as anadvertising medium they frequently contact with. Hence, it is possibleto extract an advertising medium to which users who belong to thesegment frequently contact with by utilizing the rate to be determinedby the relationship of other segment(s). Further, as to the contentrate, candidate(s) may also be determined with a value consideringadvertisement cost(s) as described in the above.

In addition, candidate(s) may further be determined by combination ofthe medium contact ratio and/or the content rate and further consideringthe costs thereto. The combination may be one of a simple AND conditionand OR condition and may be a total point calculated by multiplicationof a predetermined coefficient.

In the above-described embodiments, the CPU is used for realizing eachof the functions with programs. However, a part or entirety of thefunctions may also be realized with hardware such as logic circuit andso on.

Alternatively, a part of processing of the programs may be performed bythe operating system (OS).

A questionnaire results analysis supporting device by varying the abovedescribed embodiment. FIG. 36 shows a functional block diagram of aquestionnaire results analysis-supporting device 100. The questionnaireresults analysis supporting device 100 comprises response informationstorage means 102, search term storage means 103, determining means 104,tabulation means 105, generating means 106, search number variationhistory calculation means 107, storage means for variation history ofsearch number 108 and segment determination means 109.

The response information storage means 102 stores response informationfor questionnaire made for expressing either applied or unapplied forplural questions correspondently with respondents' IDs. The search termstorage means 103 stores a search term(s) by which a search is conductedat a specific search site correspondently with its search timing andsearcher's ID who conduct the search. The determining means 104 extractssearch timings of the search term for each searcher's ID from the searchterm storage means 103, segments the extracted search timings into apredetermined number in chronological order, and determines the userspecified by its respondent ID corresponding to the searcher's ID as theuser at each segment. The tabulation means 105 arranges each of thesegments in a direction of first axis of a cross tabulation for theitems that is responded as applied out of the response information forquestionnaire stored in the response information storage means 102 andarranges each of the items of the response information in a direction ofsecond axis of the cross tabulation and carries out cross tabulation forthe number of person belonging to the each item in each of the segments.The generating means 106 generates data arranging therein cellsbelonging to the extracted items by extracting equal or more than one ortwo items specified by the operator out of the arranged items in eitherthe first or the second axis.

Further, the generating means 106 generates data for performinghighlighted display enabling easy recognition of a cell(s) having uniquevalue(s) from other cell(s) by comparing the value of cell(s) arrangedin a direction of the first axis with that arranged in a direction ofthe second axis. In this way, highlighted display enabling easyrecognition cells having unique value(s) from other cell(s) out ofcell(s) belonging to specific item(s) arranged in a direction of thefirst axis. Further, characteristic analysis between users who conductsearch for different item(s) at different period(s) can easily beperformed when equal or more than two items are extracted.

The search number variation history calculation means 107 calculatesvariation history of search number representing chronological variationof search number for each search term stored in the search term storagemeans 103. The storage means for variation history of search number 108stores the calculated variation history of search number. The segmentdetermination means 109 determines segments in accordance with the shapeof the variation history of search number. The determining means 104extracts the searcher's ID using the segments provided from the segmentdetermination means 109.

Although, the case where the response information storage means 102 andthe search term storage means 103 are stored within one questionnaireresults analysis supporting device has been described in the abovedescribed embodiment, separate read out of these may be performed bystoring each means into separate computers. Alternatively, the casewhere the response information storage means 102 and the search termstorage means 103 may be realized with one computer.

9. Hardware Structure

The hardware structure of the questionnaire results analysis-supportingdevice 100 is similar to that of the advertising medium determinationdevice 1 shown in FIG. 2 except for the program(s) and the data storedin the hard disk 26. As shown in FIG. 37, an analysis program 126 p, asearch term storage part 126 k, a questionnaire data storage part 126 tand a search number variation history storage part 126 h are storedwithin the hard disk 26 of the questionnaire results analysis-supportingdevice 100.

In the search term storage part 126 k, user IDs and the timing ofsearches are stored as searchers' IDs who conduct searches for eachsearch term as shown in FIG. 38A. Table format in which data isorganized for each user ID is used in this embodiment, but it is notlimited to that format and data may also be stored in chronologicalorder of the timing of search as shown in FIG. 38B. In this embodiment,date of search and time instant are stored as the timing of searches,instead date of search alone may be stored. Such search timing andusers' IDs for each search term may store the search term and its searchtiming for the searches using search engines on the Internet for eachuser targeting the users who login a portal site for example.

As shown in FIG. 39, search result data is stored for each user in thequestionnaire data storage part 126 t.

For example, the user having a user ID10001 responds that these items tobe responded for the questionnaires such as “tend to pay attention onhair care”, “anxious about overly dry hair”, “tend to pay attention ondress-up”, “tend to sensitive to the fashion” as they all applied (Yes)to him/her-self.

He/she answered that the items to be responded for the questionnaires onadvertising medium “magazine B”, “TV program A”, “TV program B” and soon as they all not-applied (No) to him/her-self. He/she answered thatthe items to be responded for the questionnaires on actually recognizedadvertising medium “TV advertisement of shampoo A”, “banneradvertisement of shampoo A”, “Web-site for shampoo A” and on previouslybought product(s) “shampoo C” as they all applied (Yes) to him/her-self.

As will be described later, “date and hour”, “number of searchrespondent”, “users' IDs” for each search term are stored in the searchnumber variation history storage part 126 h as variation history ofsearch number representing chronological variation of search number bytabulating each of search terms stored in the search term storage part126 k. For example, for a search term shown in FIG. 40, one search iscarried out on 2008/5/1 by one searcher having ID of “10011”. Inaddition, three searches are conducted on 2008/5/2 by three searchershaving ID of “120303”, “10013” and “10024”. Thus, variation history ofsearch number in chronological order is recorded in the search numbervariation history storage part 126 h.

10. Analysis Processing

Analysis processing for questionnaire will be described with referenceto FIG. 41. The CPU 23 carries out input processing of object term forsearch that becomes an axis for cross tabulation (step s101). Suchprocessing may be carried out by the CPU 23 to prompt input into adialog box shown in FIG. 42 to be displayed on the monitor. The objectterm for search is set-up by inputting the search term(s) clicking abutton 134. In the below example, it is assumed that “shampoo a” isinput therein as the object term for search.

Then the CPU 23 carries out tabulation processing of search history forspecified search term(s) (step S102). The detail of tabulationprocessing is shown in FIG. 43.

The CPU 23 extracts all the records in which the search term(s) isincluded therein (step S113). In this case, the CPU extracts a searcherID “10001”, search date and hour “2008/8/5”, a searcher ID “10002”,search date and hour “2008/6/1”, a searcher ID “10003”, search date andhour “2008/7/16”, a searcher ID “10004”, search date and hour“2008/9/1”, a searcher ID “10005”, search date and hour “2008/6/24” andso on because the search term is “shampoo A”.

The CPU 23 specifies the earliest searched record within the extractedrecords (step S115). Then the CPU 23 sets the date and hour for theearliest searched period as a search date and hour of population for thesearch term (step S117). For example, in the case shown in FIG. 38A, thesearch date and hour of population for the search term “shampoo A”become 2008/5/1.

Depending on the search term being input at step S101, the search dateand hour of population therefor could be far in advance. In that case,it is possible for an operator to input arbitrary date and hour bydisplaying the search date and hour of the population calculated at stepS117 on the monitor and ask for him/her to confirmation “search date andhour of population is a certain yy/mm/dd, is it OK?”.

The CPU 23 calculates individual search timing difference by extractingthe earliest period of record after the search date and hour ofpopulation for each ID of the extracted record and records thecalculated differences (FIG. 43 step S119). In this embodiment, days areused as individual search timing differences. But, in the case of FIG.38A, the search date and hour 2008/5/1, respondent number “1”,searcher's ID “10011”, the search date and hour 2008/5/2, respondentnumber “3”, searchers' IDs “12303”, “10013” and “10024” and so on shownin FIG. 40 can be obtained as the number of respondents of searches perday and respondents' IDs. The unit for tabulation may be inputarbitrarily such as a week, a month or morning, afternoon, a certainperiod (for example three hours).

When plural searches for the same search term(s) are conducted, theearliest date thereof is the earliest search date and time for the userand the difference between the earliest search date and time and thesearch date and hour of population becomes a individual search timingdifference for the user.

Upon completion of the tabulation processing, the CPU 23 carries outsegment determination processing (FIG. 41 step S105). In thisembodiment, the steps of displaying variation history of search numberfor the search term by which the above variation history data of searchnumber is generated, chronologically segmenting such data into apredetermined number using the search timing as a key with reference tothe variation history by the operator, segmenting from the beginning ofthe search to the end thereof for the search term into a predeterminednumber, and extracting user IDs that belong to each of the segments.Such processing will be described herein.

The CPU 23 displays line charts in accordance with the above variationhistory data of search number. In this embodiment, such line chartstakes the abscissa axis and the ordinate axis respectively as dates(individual search timing differences) and the number of searches.Consequently, a tabulation segment distribution shown in FIG. 44 isdisplayed. The operator designates a method of segmentation and thenumber of segments with reference to such distribution. In this way, thenumber of segments is determined. In description below, it is assumedthat the number of segments five is designated under the segmentationbased on quantile. The segmentation based on quantile is a segmentationin which total search number is equally segmented into a predeterminedsegment number. In this case, the total number is segmented into five bydividing until each of the total reaching to 20% of the total becausethe number of segment is five. An example of post-segmentation data isshown in FIG. 45.

For the method of segmentation, various methods such as The innovationadoption curve of Rogers and so on other than the quantile may also beemployed. Further, calendar-form segmentations such as monthlysegmentation and time-segmentations starting at a search date and hourof population can also be used. Subsequently, the CPU 23 reads outquestionnaire result data (FIG. 41 step S107). In this case, it isassumed that the questionnaire result data shown in FIG. 39 is read out.

Then the CPU 23 classifies questionnaire targets in segments determinedat step S105 for plural items in the questionnaire result data, uses theresulting segments as one axis and the carries out cross tabulationprocessing using another questionnaire items as another axis (stepS109).

Conventional tabulation method can be used for the cross tabulationprocessing. In this embodiment, a cross tabulation, in which thedistribution of people is represented in percentage by employing thesegments as row of table and by employing questionnaire items as columnof table, is carried out. Consequently, the tabulation result shown inFIGS. 46 and 46 b is obtained. Specifically, the value of each item isdisplayed in percentage that is divided by the total number of peoplewho belong to a segment in this embodiment. Actually, analysis resultsin which the ratio of users belonging to segment C1 and who recognize aTV advertisement of shampoo A is 42.5% and the ratio of users belongingto segment C2 and who recognize the TV advertisement of shampoo A is54.6% and so on are obtained.

In this embodiment, cross tabulation is carried out by assigning peoplewho do not conduct search on the column of table in this embodiment (seeFIGS. 46 and 46 b). This enables an analysis that considers thecharacteristic of the people who do not conduct search.

Subsequently, the CPU 23 performs highlight display for cells havingunique value(s) (FIG. 41 step S110). In this embodiment, highlight itemprocessing data for easily recognizing from other item(s) during theirdisplay is generated for the item(s) having more than 3% higher valuethan that of the average value of each segment.

FIG. 47 shows an example of a part of such display. In this case, theaverage ratio of users belonging to segments C1 to C5 and who select theTV advertisement of shampoo A is 40.2% and belonging to segment C2 andwho select the same is 54.6%. The CPU 23 judges whether the differencebetween the value of each item and the average value has more than apredetermined value. In this case, the difference between 54.6 minus40.2 equals to 4.2, which is more than the predetermined value three. Onthe other hand, none of the differences for other segments C1 to C5exceeds the predetermined value. Therefore, the CPU 23 carries outhighlight display on a region 161 of the segment C2. The same applied toother regions 162 through 168. Such highlight display enables moreeasily recognition of characteristics of the users who belong tosegments C1 to C5.

FIG. 48 shows a display example of the overall highlight display of eachitem. An analyzer of questionnaire recognizes the facts that thequestionnaire respondents who conduct a search for “shampoo A” at earlystage largely correspond to “teens”, “tend to pay attention on haircare”, “anxious about overly dry hair”, “sensitive to the fashion” andthe ratio of contact to their contact medium such as “magazine B”, “TVprogram B” is high. In this way, analytical result, through which anadvertisement appealing hair care and overly dry hair should runthereon, is obtained. In addition, appropriate marketing strategies maybe planned because the questionnaire respondents who conduct a search atlater stage largely correspond to “thirty something” and the ratio ofcontact to their contact medium such as “TV program A” is high.

Marketing measures including more advertisements that are appropriatecan be implemented in response to timings such as before, the rightafter and after a while of releasing products even in the marketingstrategies including advertisement by practically using the tabulationutilizing search timings.

More sophisticated consumer characteristics, that can not be obtainedthrough the tabulation according to conducting search or not, can berecognized by utilizing search timings because characteristics between“a person who conducts a search at early stage when not much people knowthe product” and “a person who conducts a search at later stage whenmuch people know the product” even though these who have conductedsearches for “shampoo A”.

In addition, since those who conduct search for the product have stronginterest thereto, it is possible to recognize the timing when suchperson had participation to the product. Accurate search timing can berecognized because of its superiority of representativeness of thepopulation in light of the ratio of people who currently conductsearches on the Internet and of having variation history data of search.Further, purchase of such product or not may also be complementedthrough a questionnaire search.

Previously, there are methods of screening a consumer(s) who bought aproduct(s) from the research monitors in addition to a method ofattaching a questionnaire sheet thereto. For example, a question “haveyou bought XX before or not” is asked in advance or in the initialquestion thereof in such method and only the person who responds YES tothat question continuously responds further questions and so forth. Inthis method, however, only insufficient number of samples can beobtained when the product(s) is not popular and extra cost is requiredto do that. The present invention solve these problems even suchunpopular product.

The present invention uses the searcher who conducts a search for asearch term as one axis of cross tabulation. Consequently, aquestionnaire considering potential purchaser(s) for newly releasedproduct can be gleaned and sufficient number of samples can be securedeven when less purchaser(s) exits for the product. Previously, it isvery difficult to specify “time of purchase” data on purchase on sale(POS)/personal trading history data exists. Further, search, tabulationstring-attached to the data on purchase on sale (POS)/personal tradinghistory data either secures insufficient number of samples or tend to bebiased because distribution channels of the product and their area islimited. The present invention solves these problems and enables ananalysis that adds a tingle of the sensitivity to information.

11. Other Embodiments

In the above embodiment, the cross tabulation is obtained as a crosstabulation while performing highlight display on the cell(s) havingunique value(s), but the operator may select markings such as the typeof tabulation and highlight display. For example, it is possible todisplay a tabulation instruction input window shown in FIG. 49 prior tostep s109 in FIG. 41 and make the operator fills in the window.

In FIG. 49, the term “extracting conditions” is a pull-down menu used inthe case when limited extraction only from “teens” respondents out ofitems on row of table is desired for example, the operator selects “withconditions” and further selects “teens” from another pull-down menu.

The option “type of table” is a display format for value of each cell,and each of radio buttons such as “head-count” “estimated population”,“overall %”, “table of ranking”, and “percentage in row” is selectedwhere the operator respectively desires to display absolute head-count,to obtain estimated value representing how many people who belong toeach item nationwide using the ratio of the total number of respondents(population) out of the entire population, to display percentage ofpeople including non-searcher and to obtain the rankling of the item. Inthe case of selecting the “table of ranking”, criteria for the ranking(such as value, difference from overall mean, difference from searcheraverage, chi-square value . . . ) and so on may be selected from thepull-down menu. The option “percentage in row” is selected when theoperator desires to display in a ratio where the grand total of aspecific item assigned on the row of table is assumed as 100.

The options “items to be used for column of table” and “items to be usedfor row of table” may respectively selected from pull-down menus. In anexample shown in FIGS. 46 and 46 b, the option “items to be used forcolumn of table” represent search timing and the option “items to beused for row of table” are questionnaire items such as gender, age andso on.

For the option “about average”, one of “(overall mean)” display,“(average) non display” and “(average between searchers) display” isselected.

For the option “about marking”, criteria for judgment and thresholdvalues for carrying out the highlight display shown in FIG. 49 areinput. Upon selecting one of these, “equal or more than” and “equal orless than” and so on may also be selected as threshold values inaddition to actual values.

The CPU 23 stores the instructed conditions on each of options(“extracting conditions”, “type of table”, “items to be used for columnof table”, “items to be used for row of table”, “about average”, “aboutmarking”) input on the instruction input window shown in FIG. 49 and maydetermines output display format of a tabulation table prior to stepS109 in FIG. 41.

Display in ranking format will be described using FIG. 50. FIG. 50 is anexample of sorting the items having values reducing the average valuetherefrom in descending order in segments C1 and C2 on the tabulationresults of FIG. 48. FIG. 51 is another example of sorting only the itemsfor segments C1 to C5. Hence, a person makes analysis can recognize thecharacteristics of users belonging to respective segment with muchhigher reliability by sorting positions in accordance with the valuesreducing the average value therefrom.

Further, in the embodiments described above, tabulation is performed bygrouping the questionnaire results conducted to all the participants foreach user using the search timings, such tabulation may also be carriedout by initially grouping the users belonging to a specific group to bequestionnaire responders and use the questionnaire results responded bythe responders. For example, since users belonging to the segment C1 andconduct their searches at early stage, there might be a case in which itis desired to carry out a questionnaire is desired only to such users.In that case, more efficient questionnaire may be carried out bynarrowing the population down to a smaller number than performing thequestionnaire to all the users.

In the above described embodiment, the case where information forspecifying target attribution and data on search term are stored in thequestionnaire result analysis supporting device has been described as anexample, it is possible to configure such that one of these data or bothdata is stored in another computer (for example, a center server) andreads out such data through a network. Further, such device can also berealized as a computer system configured by three computers two of whichare divided ones from the center server.

For acquiring search results, it is possible to configure such thatinstallation of a program for storing history of using search engineswithin the user's PC is required during the user registration, storingsearch term(s) and search at each search and send them to the centerserver regularly or irregularly. In this way, well-known technique canbe employed for the method of collecting search results.

In the above described embodiment, the operator inputs the searchterm(s), the search term(s) belonging to a certain categorycorresponding to the name of advertising object can automatically bedetermined by storing search term(s) that is classified into categories.Further, they may be displayed as candidates and can be selected one ofthese.

Alternatively, its search term may be specified by carrying out thesteps of storing the variation history of search number, displaying thehistory and selecting any of the history.

Segment may be determined using a segment determination rule(s) forsegmenting into a predetermined number, wherein the segmentdetermination rule(s) is stored.

The segment may be determined using segment of search term for categoryto which a search term(s) belong, wherein the search term(s) classifiedinto category is stored.

The search terms specifying means may automatically specify a searchterm(s) including the variation history of search number similar to thatof the name of advertising object being inputted when the name ofadvertising object is input. In addition, instead of automaticspecification, it is possible to provide a search term(s) selected tothe advertising medium data determination means as a word to the name ofadvertising object.

In this embodiment, days are used for basis of various time frames, butweek, month, or even morning, afternoon, hours (for example, three hourbasis) and so on may arbitrarily be applied.

Also, segment is specified in the form of mm/dd-to-mm/dd, but it ispossible to specify segment relatively in a relative period such as onemonth later from a certain date.

As to tabulation segment, arbitrarily time intervals such as one monthand so on may be set. Further, search date and hour of population mayalso be set arbitrarily. For example, monthly tabulation will be carriedout by setting the population search date arbitrarily as January 1 andthe tabulation segment in one month. This enable to correspondence to asegment in a calendar-form.

(1) A questionnaire result analysis supporting device comprising: 1)questionnaire response information storage means for storingcorrespondently with respondents' ID questionnaire response informationresponded to one of corresponding to plural items and not correspondingthereto; 2) search term storage means for storing a search term used forconducting a search at a specific search site correspondently with itssearch timing and a searcher's ID; 3) determination means for extractingfrom the search term storage means search timing of the search term forsearcher's ID when a search term is provided as a search condition,segmenting the extracted search timing into a predetermined number inchronological order and determining a user identified by a respondent'sID corresponding to the searcher's ID as a user in each of the segments;and 4) tabulation means for arranging each of the segments in adirection of first axis of a cross tabulation for the items beingresponded as applied out of the questionnaire response informationstored in the questionnaire response information means for arrangingeach of the items of the questionnaire response information in adirection of second axis of the cross tabulation and carrying out thecross tabulation for number of person belonging to the each item in eachof the segments.

Cross tabulation of the questionnaire results can be performed accordingto the search timing of a search term.

(2) The questionnaire result analysis supporting device according to thepresent invention, wherein the tabulation means carries out a crosstabulation by additionally arranging a user who does not conduct thesearch in a direction of the first axis as a segment of non-search user.In this way, cross tabulation of the questionnaire results can beperformed according to the search timing of a search term in comparisonwith the user who does not conduct the search.

(3) The questionnaire result analysis supporting device according to thepresent invention, wherein the tabulation means carries outnormalization a value of cell belonging to a specific item out of eachcell arranged in a direction of the first axis on a cross-tabulatedtable in accordance with a value of a cell belonging to the item. Inthis way, the values of cells belonging to a specific item arranged in adirection of the first axis can be compared. Further, characteristicanalysis among users at different search timings can be made by carryingout comparison in the specific item arranged in a direction of the firstaxis plural times.

(4) The questionnaire result analysis supporting device according to thepresent invention, wherein the tabulation means carries outnormalization a value of cell belonging to a specific item out of eachcell arranged in a direction of the second axis on a cross-tabulatedtable in accordance with a value of a cell belonging to the item. Inthis way, the values of cells belonging to a specific item arranged in adirection of the second axis can be compared. Further, characteristicanalysis among users at different search timings can be made by carryingout comparison in the specific item arranged in a direction of thesecond axis plural times.

(5) The questionnaire result analysis supporting device based on thepresent invention, wherein the generating means generates data arrangingtherein cells belonging to the extracted items by extracting equal ormore than one or two items specified by the operator out of the arrangeditems in either the first or the second axis, for the tabulationresults. In this way, displays on which items desired by a person whomakes analysis for extraction, can be carried out.

(6) The questionnaire result analysis supporting device according to thepresent invention, comprising: generating means for generating displaydata arranging therein cells belonging to extracted items by extractingequal or more than one or two items specified by an operator out ofarranged items in the first axis, for the tabulation results. Thegenerating means generates data for performing highlighted displayenabling easy recognition of a cell(s) having unique value(s) from othercell(s) by comparing the value of cell(s) arranged in a direction of thefirst axis with that arranged in a direction of the second axis. In thisway, highlighted display enabling easy recognition cells having uniquevalue(s) from other cell(s) out of cell(s) belonging to specific item(s)arranged in a direction of the first axis. Further, characteristicanalysis between users who conduct search for different item(s) atdifferent period(s) can easily be performed when equal or more than twoitems are extracted.

(7) The questionnaire result analysis supporting device according to thepresent invention, comprising: generating means for generating displaydata arranging therein cells belonging to extracted items by extractingequal or more than one or two items specified by an operator out ofarranged items in the first axis, for the tabulation results in whichgenerating means generates ranking processing data for arranging in theorder of having unique value(s) from other cell(s) by comparing thevalue of cell(s) arranged in a direction of the first axis with thatarranged in a direction of the second axis. In this way, cells havingunique value(s) from other cell(s) out of cell(s) belonging to specificitem(s) arranged in a direction of the first axis can be displayed.Further, characteristic analysis between users who conduct search fordifferent item(s) at different period(s) can easily be performed whenequal or more than two items are extracted.

(8) The questionnaire result analysis supporting device according to thepresent invention, comprising: generating means for generating displaydata arranging therein cells belonging to extracted items by extractingequal or more than one or two items specified by an operator out ofarranged items in the second axis, for the tabulation results. Thegenerating means generates data for performing highlighted displayenabling easy recognition of a cell(s) having unique value(s) from othercell(s) by comparing the value of cell(s) arranged in a direction of thesecond axis with that arranged in a direction of the first axis. In thisway, highlighted display enabling easy recognition cells having uniquevalue(s) from other cell(s) out of cell(s) belonging to specific item(s)arranged in a direction of the second axis. Further, characteristicanalysis between users who conduct search for different item(s) atdifferent period(s) can easily be performed when equal or more than twoitems are extracted.

(9) The questionnaire result analysis supporting device according to thepresent invention, comprising: generating means for generating displaydata arranging therein cells belonging to extracted items by extractingequal or more than one or two items specified by an operator out ofarranged items in the second axis, for the tabulation results. Thegenerating means generates ranking processing data for arranging in theorder of having unique value(s) from other cell(s) by comparing thevalue of cell(s) arranged in a direction of the second axis with thatarranged in a direction of the first axis. In this way, cells havingunique value(s) from other cell(s) out of cell(s) belonging to specificitem(s) arranged in a direction of the second axis can be displayed.Further, characteristic analysis between users who conduct search fordifferent item(s) at different period(s) can easily be performed whenequal or more than two items are extracted.

10) A method of analyzing questionnaire result with a computer accordingto the present invention comprising the steps of: storing within acomputer correspondently with respondents' ID questionnaire responseinformation responded to one of corresponding to plural items and notcorresponding thereto; storing within a storage part a search term usedfor conducting a search at a specific search site correspondently withits search timing and a searcher's ID; the computer extracting from thesearch term storage means search timing of the search term forsearcher's ID when a search term is provided as a search condition,segmenting the extracted search timing into a predetermined number inchronological order, determining a user identified by a respondent's IDcorresponding to the searcher's ID as a user in each of the segments,and arranging each of the segments in a direction of first axis of across tabulation for the items being responded as applied out of thequestionnaire response information stored in the questionnaire responseinformation means and arranging each of the items of the questionnaireresponse information in a direction of second axis of the crosstabulation and carrying out the cross tabulation for number of personbelonging to the each item in each of the segments.

Cross tabulation of the questionnaire results can be performed based onthe search timing of a search term.

(11) A questionnaire result analysis program according to the presentinvention being a program for executing a computer the steps of: 1)storing correspondently with respondents' ID questionnaire responseinformation responded to one of corresponding to plural items and notcorresponding thereto and storing within a storage part a search termused for conducting a search at a specific search site correspondentlywith its search timing and a searcher's ID; 2) extracting from thesearch term storage means search timing of the search term forsearcher's ID when a search term is provided as a search condition,segmenting the extracted search timing into a predetermined number inchronological order, determining a user identified by a respondent's IDcorresponding to the searcher's ID as a user in each of the segments;and 3) arranging each of the segments in a direction of first axis of across tabulation for the items being responded as applied out of thequestionnaire response information stored in the questionnaire responseinformation means and arranging each of the items of the questionnaireresponse information in a direction of second axis of the crosstabulation and carrying out the cross tabulation for number of personbelonging to the each item in each of the segments.

(12) A questionnaire result analysis system according to the presentinvention, the system executing the steps of: storing within a firstcomputer correspondently with respondents' ID questionnaire responseinformation responded to one of corresponding to plural items and notcorresponding thereto; storing within a second computer a search termused for conducting a search at a specific search site correspondentlywith its search timing and a searcher's ID; and extracting by a thirdcomputer from the second computer search timing of the search term forsearcher's ID when a search term is provided as a search condition,segmenting the extracted search timing into a predetermined number inchronological order, determining a user identified by a respondent's IDcorresponding to the searcher's ID as a user in each of the segments,and arranging each of the segments in a direction of first axis of across tabulation for the items being responded as applied out of thequestionnaire response information stored in the first computer andarranging each of the items of the questionnaire response information ina direction of second axis of the cross tabulation, and carrying out thecross tabulation for number of person belonging to the each item in eachof the segments; the third computer being connected to the firstcomputer and the second computer.

Cross tabulation of the questionnaire results can be performed based onthe search timing of a search term.

(13) A questionnaire participant determination device according to thepresent invention comprising: 1) questionnaire response informationstorage means for storing correspondently with respondents' IDquestionnaire response information responded to one of corresponding toplural items and not corresponding thereto; 2) search term storage meansfor storing a search term used for conducting a search at a specificsearch site correspondently with its search timing and a searcher's ID;3) determination means for extracting from the search term storage meanssearch timing of the search term for searcher's ID when a search term isprovided as a search condition, segmenting the extracted search timinginto a predetermined number in chronological order, determining a useridentified by a respondent's ID corresponding to the searcher's ID as auser in each of the segments; and 4) questionnaire participantdetermination means for determining a searcher's ID belonging to thesegment as a questionnaire participant when any of the segment isspecified.

In this way, a questionnaire to prospectively limited participants canbe carried out based on the search timing of a search term. Hence, aquestionnaire for its purpose can be carried out by limitingparticipants thereof.

In the above described embodiments, items assigned on the column oftable and items assigned on the row of table are respectively employedas the first axis and the second axis of the cross tabulation table,“the column of table” and “the row of table” are interchangeable witheach other.

The term “a cell(s) having unique value(s)” refers to the cases suchthat the value representing whether or not the items of cross tabulationresult being statistically significant and the value(s) subtracting theaverage value of each segment from the value(s) of each cell is muchlarger value(s) and much smaller value(s) than that of other cell(s).The terms also refer to the cell having a larger chi-square value(s) forthe item(s) of the cross tabulation result.

In the above disclosure, the present invention has been described aspreferred embodiments, each of the terms therein is used forillustrative only and is not limitative, such terms may be amendedwithout apart from the scope of the invention being limited solely bythe claims appended hereto.

What is claimed is:
 1. An advertising medium determination devicecomprising: target specifying information storage means for storingcorrespondently with searchers' identification information forspecifying target attribution including information for specifyinginformation delivery medium of an object to contact with; search termstorage means for correspondently storing searchers' identifications,timing of search and search terms used for the search; extraction meansfor extracting a timing of search for a search term for each searcher'sidentification from the search term storage means when the search termis provided as a search condition and segmenting the extracted searchtiming into a predetermined number in chronological order and extractingsearcher's identification belonging to each segment; and advertisingmedium data determination means for extracting candidates of informationdelivery medium for the each segment from the extracted each searcher'sidentification using information for specifying a target stored in thetarget specifying information storage means for determining one or morethan two representation candidates of information delivery medium fromthe extracted candidates of information delivery medium, therebydetermining the representation candidates of information delivery mediumarranged in chronological order as advertising medium data in a name ofadvertising object provided correspondently to the search term.
 2. Theadvertising medium determination device according to claim 1, furthercomprising: search term specification means for specifying a search termcorresponding to the name of advertising object and providing thespecified search term to the extraction means while providing a termcorresponding to the name of advertising object to the advertisingmedium data determination means when such term is provided thereto. 3.The advertising medium determination device according to claim 2,wherein the search term stored in the search term storage means isclassified into categories, and wherein the search term specificationmeans specifies a search term of a category into which a termcorresponding to the name of advertising object belong thereto.
 4. Theadvertising medium determination device according to claim 1, furthercomprising: search term specification means for providing a search termcorresponding to the name of advertising object to the extraction meanswhile providing the name of advertising object to the advertising mediumdata determination means when the name of advertising object and asearch term corresponding thereto is provided.
 5. The advertising mediumdetermination device according to one of claim 1, further comprising:segment determination means for storing a segment determination rule forsegmenting into the predetermined number, wherein the extraction meansextracts the searcher's identification using the segment determinationrule provided from the segment determination means.
 6. The advertisingmedium determination device according to claim 1, wherein the segmentdetermination means displays the variation history of search number anddetermines a segment using the provided segment data.
 7. The advertisingmedium determination device according to claim 1, wherein the searchterm stored in the search term storage means is classified intocategories, and the device further comprising: segment determinationmeans for determining a segment under the segment of the search term ofa category to which the search term belongs therein.
 8. The advertisingmedium determination device according to claim 2, further comprising:search number variation history calculation means for calculatingvariation history of search number representing chronological variationof the number of search for each search term stored in the search termstorage means; and search number variation history storage means forstoring variation history of the number of search; wherein when a nameof advertising object is input as an object to be corrected the searchterm specification means specifies a search term that includes searchnumber variation history similar to the search number variation historyof the inputted name of advertising object and provides the specifiedsearch term to the advertising medium data determination means as theterm corresponding to the name of advertising object.
 9. The advertisingmedium determination device according to claim 2, further comprising:search number variation history calculation means for calculatingvariation history of search number representing chronological variationof the number of search for each search term stored in the search termstorage means; and search number variation history storage means forstoring variation history of the number of search; wherein when a nameof advertising object is input as an object to be corrected the searchterm specification means specifies a search term that includes searchnumber variation history similar to the search number variation historyof the inputted name of advertising object, displays the search numbervariation history of the specified search term, and when any search termis selected, provides the selected search term to the advertising mediumdata determination means as the term corresponding to the name ofadvertising object.
 10. The advertising medium determination deviceaccording to claim 2, wherein the search terms used as the searchcondition are a plurality of search terms combining one of logical andlogical add or both of these, and wherein the extraction meanscalculates a period from the beginning of search to the end of thesearch for each search term and extracts searcher's identificationbelonging to each segment by carrying out calculation based on thesearch condition.
 11. The advertising medium determination deviceaccording to claim 10, wherein the calculation performed based on thesearch condition is a logical and operation to be provided.
 12. Theadvertising medium determination device according to claim 10, wherein alogical and operation out of the calculations based on the searchcondition calculates the maximum value of a period.
 13. The advertisingmedium determination device according to claim 10, wherein a logical andoperation out of the operations based on the search condition calculatesthe average value of a period.
 14. The advertising medium determinationdevice according to any of claim 10, wherein the extraction meanscarries out the calculation after normalization of the period about eachof the obtained search terms on a search term to search term basis. 15.The advertising medium determination device according to claim 14,wherein the normalization is carried out through segmentation of thebeginning of search to the end of the search for each search term in apredetermined number and through a logical and operation depending on towhich segment the segmented frame belonging to.
 16. The advertisingmedium determination device according to claim 15, wherein when data outof the normalized data of each of the search terms that is subject tological and operation differs from other data equal or more than apredetermined threshold value, a logical and operation is carried outwith ignoring such normalized data.
 17. The advertising mediumdetermination device according to claim 16, wherein when no searchtiming exists, a term such as differs from equal or more than apredetermined threshold value is used.
 18. The advertising mediumdetermination device according to claim 10, wherein when no searchtiming exists in a search term that is subject to a logical andoperation, a logical and operation is carried out with ignoring of suchsearch term if the number of such search is equal or less than apredetermined number.
 19. A method of determining advertising medium,the method comprising the step of: storing within a computer informationfor specifying target attribution including information for specifyinginformation delivery medium of an object to contact with correspondentlywith searchers' identification, and data on a search term thatcorresponds a searcher's identification performing a search, a timing ofthe search, and the search term with one another; wherein when a searchterm is provided, the computer extracts the timing of search for suchsearch term from a search term storage means, segments the extractedsearch timing for each searcher's identification into a predeterminednumber in chronological order and extracts searcher's identification ineach segment, and wherein the computer extracts a candidate ofinformation delivery medium for the each segment from the extractedsearcher's identification using the stored information for specifyingtarget and determines one or more than two representative candidate ofinformation delivery medium from the extracted candidate of informationdelivery medium, thereby the candidate of information delivery mediumarranged in chronological order of the each segment is determined asadvertising medium data in the name of advertising object providedcorrespondently to the search term.
 20. An advertising mediumdetermination device comprising: extraction means for extracting fromsearch term storage means storing therein a searcher's identification,the timing of search, and the term used for the search the timing ofsearch for such search term for each searcher's identification,segmenting the extracted search timing for each searcher'sidentification into a predetermined number in chronological order andextracting searcher's identification in each segment; and advertisingmedium data determination means for extracting information on candidateof information delivery medium for the each segment from the extractedeach searcher's identification using information for specifying targetattribution including information for specifying information deliverymedium of an object to contact that is stored correspondently withsearchers' identification, determining one or more than tworepresentative candidates of information delivery medium from theextracted candidates of information delivery medium, thereby determiningthe candidate of information delivery medium arranged in chronologicalorder of the each segment as advertising medium data in the name ofadvertising object provided correspondently to the search term.